It is known that in computerized tomography (CT) images, the intensity level may be used for distinguishing different types of tissue. A CT system may be calibrated such that the intensity values correspond to Hounsfield units (HU) as given in the table below:
IntensityTissuevalue [HU]Bone1000 Liver40-60White matter in brain46Gray matter in brain43Blood40Muscle10-40Kidney30Cerebrospinal fluid15Water 0Fat−50-100Air−1000   
The Hounsfield units normally range from −1000 to 3000, but in some applications the HU scale is shifted into values between 0 and 4000.
As is apparent from the table above, examination of different types of tissue requires the inspection of different intensity value ranges, also referred to as intensity windows.
Due to the limitations of display screens, and also to limitations of the human eye, it is common to display a maximum of 256 (28) different gray values or shades on the display screen. Hence, in order to obtain a useful view of a CT image showing tissues having intensity values close to each other, it is necessary to display only a limited portion of the total HU scale.
In the following, the displayed or processed intensity value range will be referred to as an ‘intensity window’. If e.g. bones are examined one typically chooses a very wide window width of 1000-2000 HU, whereas for the examination of soft tissue, more narrow window widths of 400-600 HU are used and for brain examinations very narrow window widths of 50-100 HU are common.
Due to the different anatomies viewed and the very different intensity ranges, the different cases require different noise reduction and contrast enhancement treatment. However it is still desirable to store the result in one image and be able to switch between intensity windows in case different tissues are to be examined.
In U.S. Pat. No. 5,594,767, an original CT image is combined with a smoothed version of the original CT image, the combination being based on a classification map. The smoothed image is non-selectively smoothed, i.e. it smoothes the entire image, regardless of the values of the respective image elements.